2 edition of Automatic pattern recognition of meteorological satellite cloud photography found in the catalog.
Automatic pattern recognition of meteorological satellite cloud photography
Yale H. Katz
Includes bibliographical references.
|Statement||by Y.H. Katz and W.L. Doyle.|
|Series||Research memorandum -- RM-3412, Research memorandum (Rand Corporation) -- RM-3412..|
|Contributions||Doyle, W. L.|
|The Physical Object|
|Pagination||89 p. :|
|Number of Pages||89|
and nasa technical nasa tt f translati z co i-s (nasa-tt-f) meteorological n interpretation of space photographs of the earth (quantitative methods) (linguistic. A novel method for removing thin clouds from single satellite image is presented based on a cloud physical model. Given the unevenness of clouds, the cloud background is first estimated in the frequency domain and an adjustment function is used to suppress the areas with greater gray values and enhance the dark objects. An image, mainly influenced by transmission, is obtained by subtracting.
Research Article Automatic Tracking and Characterization of Cumulonimbus Clouds from FY-2C Geostationary Meteorological Satellite Images YuLiu, 1,2 Du-GangXi, 3 Zhao-LiangLi, 4,5 andChun-XiangShi 6 Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. The goal was to train machine learning for automatic pattern recognition. MiniBooNE particle identification: This dataset is taken from the MiniBooNE experiment and is used to distinguish electron neutrinos (signal) from muon neutrinos (background).
objective cloud type identification is possible, however, identification considering meteorological conditions and cloud patterns is difficult. On the contrary, cloud type identification by the human eye has the merit of being able to use meteorological conditions, cloud patterns, changes with time, and other comprehensive meteorological Size: 1MB. Satellite data shows the global cloud region in visible and infrared ranges, but have an uncertainty in terms of weather events and large time interval between the two periods of measurements, which complicates the use of this information for very short range forecasts of weather by: 3.
Applied Relaxation Training
CAS printed access tools
churches role in the development of Ovamboland
Sea Lion Roars (Smithsonian Oceanic Collection)
huge leap forward
Area handbook for Syria.
Census of population, 2000
Sculptured for eternity
All about a London daily from the paper mill to the breakfast table.
The thrill of it all
Introduction to Eastern European-foreign joint ventures
Systems in action
Europeanization and multilevel governance
Leonardo da Vinci
Some mechanical procedures for automatically recognizing and classifying specific cloud patterns from satellite photography are described and several data reduction transformations that have detected and isolated certain Automatic pattern recognition of meteorological satellite cloud photography book in which cloud "streets" differ from randomly placed cloud elements.
Cloud Verification The first step of the verification process is to incrementally shiftthe initial cloud detection mask in the theoretical direction of the sun’s raysprojected in the image plane.
Thesun azimuth angle is easily known through knowledge of the time and position of the satellite when the image was acquired; which, in theFile Size: KB. Catalog of meteorological satellite data--ESSA 9 television cloud photography (v.1) [Unknown.] on *FREE* shipping on qualifying offers.
Catalog of meteorological satellite data--ESSA 9 television cloud photography (v.1). According to the characteristic that the gray value difference is quite obvious in different areas of the singles infrared cloud, this paper puts forward an algorithm of the eyed typhoon's center automatic positioning.
After pretreating the cloud image, we use the template to segment the airtight cloud wall area which has high gray value. In addition, the difference between gray values of the Cited by: 1. Develop and test a cloud classification technique based on pattern recognition meth- ods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery.
Develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of changeFile Size: 1MB. We propose the automatic generation of the ortho-photo data which support realistic scenes for DEM by texture mapping.
This ortho-photo data is automatically generated by pattern recognition techni Author: LeeEun-Seok, JeongYoung-Sik, HassanHoucine, ShinByeong-Seok, ParkJong Hyuk. In this chapter, we will discuss some basic concepts about pattern and pattern recognition dealing with biometrics, as well as an illustrated general configuration of pattern recognition system.
Then, the techniques for image segmentation, including pixel classification, gradient-based segmentation, and edge detection, are reviewed in Section The analysis of the typhoon is based on the manual pattern recognition of cloud patterns on meteorological satellite images by human experts, but this process may be unstable and unreliable, and we think could be improved by taking advantage of both the large collection of past observations and the state-of-the-art machine learning methods, among which kernel methods, Cited by: 4.
Automatic procedures usually take charge of low- and middle-level tasks, relieving human experts from part of the work. An example of a partly automated task is the tracking of meteorological structures, which is usually performed using techniques based on local correlation between pixel intensity by: 2.
Highlights A whole sky imaging system is used for the estimation of cloud classification. A multi color criterion is applied to detect broken and overcast clouds.
A simple method is presented for the detection of raindrops. The success of the classifier ranges between 78 and 95% for seven cloud by: The improved method has been tested using rapid-scan observations of Hurricane Eloise obtained by the GOES satellite on 22 September We performed cloud tracking using target selection (clustering) based either on visible or infrared data and tracked the targets using a pattern recognition by: Katz, Y.H., “Pattern Recognition of Meteorological Satellite Cloud Photography” Proc.
Third Symposium on Remote Sensing of the Environment, Institute of Science and Technology, University of Michigan – ().Cited by: 3. Automatic satellite image analysis methods that can find storm-related cloud patterns are thus in demand.
We propose a machine learning and pattern recognition-based approach to detect “comma-shaped” clouds in satellite images, which are specific cloud distribution patterns strongly associated with cyclone : Xinye Zheng, Jianbo Ye, Yukun Chen, Steve Wistar, Jia Li, Jose A.
Piedra Fernández, Michael A. Stein. The detecmination of cloud pattern motions from geosynchronous satellite image data. J.A., and Epstein, E.S. Application of two-dimensional spectral analysis to the quantification of satellite cloud photography. Appl. Meteorology 2 (Oct.
), Google Scholar Cross Ref; Katz, Y.H. Pattern recognition of meteorological Author: P StrongJames, RosenfeldAzriel. Yale H. Katz. Nuclear war and soil erosion: some problems and prospects Automatic pattern recognition of meteorological satellite cloud photography About RAND Reports.
Quality Standards; Publishing Overview; Ordering Information; Information for. This investigation has attempted to discover appropriate texture descriptors and to reveal more clearly the importance of texture analysis techniques for multispectral cloud classification.
The textural features considered in this study include both spatial and frequency features. The spatial features were mainly those based on spatial grey-level difference statistics and circular Moran Cited by: In the context of pattern recognition, a pattern is a vector of features describing an object.
This pattern is made up of measurements on a set of features, which can be thought of as the axes of a k-dimensional space, called the feature space. The aim of pattern recognition is to establish a relationship between a pattern and a class by: Y.H.
KatzPattern recognition of meteorological satellite cloud photography Proc. Third Symposium on Remote Sensing of Environment, Institute of Science and Technology, Univ. of Michigan (February ), pp.
Cited by: Pattern Recognition is a mature but exciting and fast developing field, which underpins developments in cognate fields such as computer vision, image processing, text and document analysis and neural networks. It is closely akin to machine learning, and also finds applications in fast emerging areas such as biometrics, bioinformatics.
Automatic Classification Satellite images for weather Monitoring 3, views. Share; Like Automatic Classification Satellite images for weather Monitoring of Object Recognition Relations between PR and IP Diagram of Object Recognition Image Processing Images Data Analysis Pattern Recognition Pattern Recognition Object Classes Image.
The central themes of this book are informationand scale. The approach is astronomydriven, starting with real problems and issues to be addressed.
We then proceed to comprehensive theory, and implementations of demonstrated eﬃcacy. The ﬁeld is developing rapidly. There is little doubt that further important papers, and books, will follow in.Cloud detection and analysis from satellite images has been a topic of research in many atmospheric and environmental studies; however, it still is a challenging task for many reasons.Pattern Recognition of Satellite Cloud Imagery for Improved Weather Prediction Pattern Recognition of Satellite Cloud Imagery for Improved Weather Prediction  Submitted by drupal on Tue, 10/22/ - Firm: Chase Consulting Inc  Award Solicitation: NASA SBIR Phase I Solicitation  Award ID: SBIR_85_P1_ Award Dollars: